Joan Santoso

Institut Sains dan Teknologi Terpadu Surabaya

Papers

Total Citations

H-Index

About

Joan Santoso’s research lies at the intersection of artificial intelligence and game theory, with a focused interest in developing intelligent agents for strategic gameplay. Their most cited work, "Evolutionary Neural Network for Othello Game" (2012), which has garnered 4 citations, introduces a novel approach to game-playing AI by combining evolutionary algorithms with neural networks. This contribution demonstrates how computational models can mimic human decision-making processes, enabling an AI to compete against human players in the classic board game Othello. By studying the thought processes of human beings and representing them through adaptive neural architectures, Santoso’s work offers a compelling glimpse into how machines learn strategy and adapt over time. While their citation count reflects a niche but dedicated audience, the research underscores a foundational effort in evolutionary computation for game AI. For students and researchers exploring the synergy between evolutionary methods and neural networks, Santoso’s work serves as an early, insightful example of how artificial intelligence can be trained to master complex, turn-based games through iterative learning and optimization.